forensic analysis - empower tech days 2013

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Network Monitoring & Forensics Empower Tech Days Mennouchi Islam Azeddine Consultant at ITS http://www.infotoolssolutions.dz [email protected] 1

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Forensic Analysis presented by Mennouchi Islam Azeddine

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Page 1: Forensic Analysis - Empower Tech Days 2013

Network Monitoring & Forensics

Empower Tech DaysMennouchi Islam Azeddine

Consultant at ITShttp://[email protected]

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Page 2: Forensic Analysis - Empower Tech Days 2013

Network Forensics Usefulness Intro to forensic data types Working with PCAP data

What it looks like How to interpret it How to get it

Working with flow data What it looks like How to interpret it How to get it

Agenda

2

Host Forensics PCAP and flow recap Working with logs and alerts

What they look like How to interpret them Getting them all in one place SIEM’s and their familiars

Fielding a monitoring solution

Page 3: Forensic Analysis - Empower Tech Days 2013

Introduction

Network forensics is the capture, recording, and analysis of network events in order to discover the source of security attacks or other problem incidents.

Course Goal: To give the student a broad understanding of the main types of network forensic data gathering and an introduction to low level concepts necessary for a proper understanding of the task of performing network forensics. After completion, a student should be able to plan and execute a reasonable network monitoring program and use the gathered forensic data to perform a wide range of investigations.

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Benefits

Why do you care

• If this isn’t in your toolbelt already, you’ll get a lot of new capabilities when you go on a project.

• If you’re already seasoned, you can learn from everyone else here.

Why do I care

• The Socratic method works. 4

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Disclaimer

The information and views presented during this course concerning software or hardware does not in any way constitute a recommendation or an official opinion. All information presented here is meant to be strictly informative. Do not use the tools or techniques described here unless you are legally authorized to do so.

This presentation is Based on OpenSecurityTrainning.info

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Performing Network ForensicsWhat do we need to know?

What does our network even look like?

Are we being attacked?

Is anything compromised?

How did it get compromised?

Where are the attacks coming from?

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Performing Network ForensicsWhat do we have to work with?

Loads of recorded network data (PCAP and flow)

Logs and alerts from security products

Logs from applications

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Main types of forensic data

We’ll be grouping forensic data into three main data types based on the tools and analysis techniques used

• Full packet capture (PCAP)

• Flow data (netflow, IPFIX, etc.)

• Log / alert data (giant text files)8

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Forensic Data Type #1Full Packet Capture (PCAP)

A full copy* of a set of packets travelling over the network

The most complete form of monitoring possible

Takes up a lot of space

*it’s possible to do partial captures, too 9

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Forensic Data Type #2Flow Data

Records of conversations on the network

Stores info such as time, duration, number of packets, total bytes sent, received, etc.

Does not contain any application layer data

Good for understanding how data flows on your network quickly

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Forensic Data Type #3Log/Alert data

Any text that gets written to a file that we can monitor

Some of it is very important (firewall alerts, availability alerts, etc.) and some of it is less so

We have to set up things to produce GOOD alerts

There are a lot of log sources, so some sort of management is preferable

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Forensic Bonus DataPeople

This is when someone comes up to you and tells you that they can’t connect to the network, the mail server is down, etc.

Pretty darned close to real time

Hard to digitize…

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Forensic Data Type ComparisonHow do they differ?

Collection Storage What it can reveal

Tools used to Analyze

Typical use

PCAP Done by machines on the network, taps, and anything that can read 1’s and 0’s off the network

Consumes lots of disk space. For a project of any size, you’ll have to spend money on a storage solution.

Exactly what went across the network.

Wireshark, Firewalls, Content Filters, etc.

Deep dive, finding out exactly what commands were issued and how compromises occurred.

Flow Done by apps on computers on the network or by decent routers

Low space requirements, so it’s easy. Generally unified for large networks.

Patterns about conversations, amount of data sent, time, etc.

Silk, Argus, etc.

Retrospective analysis, finding attackers and compromised machines.

Log/Alert Done by whatever app creates them, wherever it’s set to write them.

Generally either left where they were created or consolidated by a log manager or SIEM

Events that occur and are noticed by some piece of software, e.g. attacks, outages, etc.

Splunk, Arcsight, SIEM’s

Alerting us to major problems when they occur (or as soon as our log handling methodology shows it to us) 13

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So what do we capture and when?

Whatever they’ll let you capture

• A lot of times the people/systems that you’re working with will be totally opposed to you actually using the network for anything because the world might end or people might explode. I’ll try to give you ways to work your way around this.

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So what do we capture and when?

First get your easy wins

• Turn on flow data recording on your switches and routers and pump it to some machine.

• Figure out what log and alert sources are already present and get them into a log manager.

Now you’ve got some flow data and some log/alert data! For free(-ish)!

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So what do we capture and when?

Find out what you’re missing

• Look at your network diagram and if there’s any part where you’re not getting data from, toss a sensor out there.

Look at your data and find trouble spots

• Find events/hosts of interest by analyzing the flow and log data that you’re getting. (More on how to do this later.)

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So what do we capture and when?

Increase monitoring in trouble spots

• Grab PCAP data from links where you think compromises are occurring.

• Set up IDS/SIEM/etc. products to produce alerts tailored to the problems you see.

• Throw host based monitoring apps on suspect machines.

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So what do we capture and when?Breakdown

Log/alert data: Whenever possible, and particularly once you’ve tweaked your alerts.

Flow data: Whenever possible. It’s easy to capture and easy to work with.

PCAP data: When you need to look closer than flow or log/alert data allows OR when you have tons of resources to blow on disk space.

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How you’ll typically start an investigation

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SIEM pops up an alert to your screen, fellow coworker, cell phone, etc saying “Something is horribly wrong on host X!”

You then go look at other logs on host X. Maybe you find something scary. Maybe you can’t see the forest for the trees.

Then you open up your flow data for the time in question. See any patterns? Identify suspicious conversations, capture the packets (if you can) and investigate further. Mount some sort of defense against whatever you find.

OR

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How you’ll typically start an investigation

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Somebody hands you a big pile of PCAP or flow data.

Put it through an app to create flow data or IDS alert data (if you don’t have it already)

Look for patterns using some analysis tool. Focus down to specific data using those patterns or human reports of problems and get as close to the problem as possible.

Figure out what kind of monitoring you need to get the data you truly need to find the problem, catch the bad guy, or get the conviction. Then go deploy it, assuming you can get client buy-in. (or… create ticket, walk away)

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How we’re going to learn this

We’ll be exploring the data types starting at the most finely grained (PCAP) and working up, so that we’ll better understand the limitations of each type, even though in a real investigation, you’d end up using the data in the reverse order.

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PCAP dataThings to think about

PCAP is a straight copy of ALL* network traffic that flows through the pipe for as long as you keep recording. That can be a LOT of data!

How long do you need to listen?

Can your NIC capture it fast enough?

Can your hard drive store it fast enough?

How long can you listen before you have to free up space?

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PCAP dataLine speed and storage

Link type mb/s ~MB/s ~GB/day

Ethernet 10 1 87

Fast Ethernet

100 10.1 875

OC-12 622.08 63 5,446

Gigabit Ethernet

1,000 101.3 8,755

OC-48 2,488.32 252.1 21,785

10 Gigabit Ethernet

10,000 1,013.3 87,547

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Keep in mind, a single width PCI slot can handle, at most, 133 MB/s. Past that you’ll need PCI-E NIC’s to capture.

Also, commodity hard drives are going to have a maximum write speed around 125 MB/s on a good day.

You’ll likely need to either limit your capture time, or spend some money on a RAID solution.

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PCAP dataWhat does it look like?

24Source: screenshot of wireshark interface

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PCAP dataHow we get it

Network taps

• Devices that are connected between two other network devices

• Passively monitors traffic, and reproduces it on one or more monitor ports

• Available for all media types and speeds

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PCAP dataHow we get it

Network taps

26Source: netoptics.com, hackaday.com

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PCAP dataHow we get it

SPAN ports

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Source: datacomsystems.com

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PCAP dataHow we get it

Direct capture from the NIC on a machine

• You’ll always do this at some point.

• Very easy and convenient in low traffic settings. Just start capturing to the hard drive and stop when you feel like it.

• Storage becomes an issue when (traffic * time) > hard drive capacity OR (traffic / time) > hard drive write speed

• Can only see the traffic going to that host (so use taps or SPAN ports to gain visibility)

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PCAP dataHow we get it

Direct capture from the NIC on a machine

• tcpdump

• wireshark

• Netwitness

• etc.

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Network coverage – an aside

Network coverage is how much of the traffic on the network that your sensor network can see. You can have different types of monitoring on different parts of the network, but the main idea is to avoid blind spots. This applies to PCAP, flow, logs, and everything else.

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Network coverage – an aside

Since different segments of the network carry different traffic, where you decide to place you sensors will determine what you can see.

What would you see on the outside of the border firewall that you wouldn’t see inside? What kinds of things do you WANT to see?

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Network coverage – an aside

Things to think about

NAT – solve with placement of sensors

VPN – solve with placement of sensors or VLAN specific configuration

Multiple border gateways – solve using channel bonding/aggregation

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Network coverage – an aside

On the outside of your firewall, you see the attacks that didn’t get through in addition to the things that did. On the inside of your firewall you see things that actually got through. The outside tells you who’s attacking and how. The inside tells you what attacks worked.

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Network coverage – an aside

In addition to the amount of the network that’s covered, we can also think about WHEN the network is being covered.

Sometimes you’ll want PCAP data for a couple of hours, but couldn’t handle 24/7. When might that be? Could you perhaps trigger full PCAP for a time based on some event? Absolutely!

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PCAP dataHands on

Now that we know where, why, and how to collect PCAP data, let’s go do some captures.

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PCAP dataDoing analysis - Wireshark

Wireshark is your good old fashioned, run of the mill, go-to, protocol analyzing, packet capturing, file carving buddy. Learn to love it.

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PCAP dataDoing analysis - Wireshark

What we’ll be doing today

• Learning the layout of the interface

• Capturing PCAP data

• Looking at the structure of packets

• Filtering packets to find interesting things

• Following a TCP session

• Carving files

• Reading emails

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PCAP dataDoing analysis - Wireshark

Sources for pcaps

• http://wiki.wireshark.org/SampleCaptures

• http://packetlife.net/captures/

• http://www.pcapr.net

• http://www.icir.org/enterprise-tracing/download.html

• Your own machine 38

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PCAP dataDoing analysis - Wireshark

So that’s Wireshark. Pretty nice, huh? When it comes to finding out exactly how your machine got pwned (aka owned, pwnt, etc.), it’s pretty effective.

Also, the functionality of Wireshark can be extended by coding up plugins and decoders, and anything else you want. It’s open source!

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PCAP dataDoing analysis - Wireshark

But what if we don’t have time to do all that poking about and sifting through packets? Is there a better way to look through a big pile of PCAP data?

I thought you’d never ask…

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PCAP dataDoing analysis - Netwitness

What we’ll be doing today

• Learning the interface

• Importing some PCAP data

• Doing (almost) everything we just did in Wireshark in less time than it took us before

• Catching things that we might have missed before

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PCAP dataDoing analysis - Netwitness

Netwitness is a tool for getting a quick picture of what someone was doing on the network, especially if you’re going after less advanced threats, like insider threats or the average criminal.

Currently there’s a freeware version and a paid version. Give it a try next time you get stuck during an investigation. Often you can catch certain clues via the session based view that you wouldn’t simply by digging through PCAPs.

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PCAP dataDoing analysis – Other tools

In addition to sitting down and doing deep dive analysis on PCAP data by hand, we can also run it through automated processes (sometimes even at line speed!) to do all sorts of other stuff. This is how firewalls and IDS work, after all.

Depending on the audience, this is where we discuss our organization’s custom tools

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PCAP dataGenerating flow and alert data

Useful when someone hands you a big wad of PCAP and you have no other data

Can be done when you’ve got data from before you fielded your flow monitoring or alert generating apps (IDS, firewall, etc.)

Makes analysis of large data sets easier since it’s faster to look at coarse grained data.

We’ll cover this when appropriate.

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PCAP DataConclusion

When you have PCAP you can see pretty much everything.

It’s very heavy weight whenever you start dealing with enterprise level networks.

It’s the only way you’ll see what’s being said on the network, but it’s not as good as flow or log/alert data for figuring out what’s important to look at.

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Page 46: Forensic Analysis - Empower Tech Days 2013

Day 1 Agenda and motivation Intro to forensic data types Working with PCAP data

What it looks like How to interpret it How to get it

Working with flow data What it looks like How to interpret it How to get it

Agenda

46

Day 2 PCAP and flow recap Working with logs and alerts

What they look like How to interpret them Getting them all in one place SIEM’s and their familiars

Fielding a monitoring solution

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Flow dataThings to keep in mind

This is easy data to get, so make sure you do.

Better used to figure out where to look, than to figure out exactly what happened.

Even when you’re not on an investigation, you should collect flow data to do baselining.

Visualization helps a lot.

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Flow dataWhat is flow data?

There’s some variation, but generally a record contains the following:

Source and dest ip

Source and dest port

Protocol

Start time + (duration | end time)

# of packets

# of bytes

Directionality? Depends on format.

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Flow dataNetflow v5 protocol

49Source: caida.org/tools/utilities/flowscan/arch.xml

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Flow dataCommand line output

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Flow dataDirectionality

Some types of flow records are unidirectional (SiLK, rw tools), and others are bidirectional (argus, ratools, original flow data).

Unidirectional flow data has a separate record for both sides of the conversation. This is how Cisco NetFlow v5, v9, and IPFIX records are specified.

Bidirectional flow data combines both sides into one record, usually having extra fields for “# of sender packets”, “# of destination bytes”, and other things that would get muddled by combining two unidirectional flows. 51

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Flow dataDirectionality

Depending on what you need, you can convert between bidirectional and unidirectional using whatever tool is appropriate to your data set.

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Flow dataCutoff and Aging

Until conversations end, their flow data sits in the router/switch/etc. memory, taking up space (DOS?). So if we’ve got lots of very long lived flows or flows that didn’t end well (FIN ACK) we need to free up that memory and write the flows.

For long flows, we have a configurable time (say 30 minutes) after which we write a record and start a new one. Figuring out how long the flow actually was will require massaging your data.

For broken flows, another cutoff time (maybe 15 seconds?) will clear them out.

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Flow dataSampling

When there’s too much traffic for your switch, NIC, or whatever to handle, sampling is used to throttle the workload.

Instead of every packet being recorded in a flow (sample rate = 1 out of 1), we take 1 out of N packets, make flow records, and then scale the appropriate values by N.

We will miss flows due to this but for very large throughputs it’s necessary. Also, N is not always constant over time.

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Flow dataFormats

And then there are different formats…

Cisco NetFlow v5 and v9 are very common. V5 will only do IPv4, though.

IPFIX is a lot like v9 plus some interesting fields. Open protocol put out by IETF.

sFlow hardware accelerated, forced sampling, mainly an HP thing.

And there are others, but we’ll focus on v5/v9 and IPFIX.

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Flow dataFormats

There isn’t a current standard for how to store flow data on disk, so different software suites will store it differently to suit their search and compression capabilities. Choose your software suite based on what formats it can consume, and be prepared to perform a conversion if you switch.

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Flow dataCapturing

Switches and routers

• Flow data is gathered by the network hardware, and then sent over the network to one or more listeners.

• To set up collection and forwarding, look up instructions particular to your device and the revision of its OS (typically Cisco IOS).

• Remember, this is going over the network, so it can be intercepted, falsified, or blocked by attackers, outages, and misconfigurations!

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Flow dataCapturing

Machines on the network

• Creates flow data based on what network traffic that machine can see.

• Can either generate flow data and forward it to another collector, store it locally, or both.

• Also possible to collect flow data from other machines or network hardware.

• Eventually your flow data will have to end up somewhere. You want that somewhere to be handy to your analysts.

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Flow dataAnalyzing with argus

Argus is another popular tool which is much easier to deploy, so we’ll be using it to do some sleuthing.

• Become familiar with a few of the tools

• Locate a scanning machine

• Detect beaconing

• Find activities by a compromised machine

• Find routing misconfigurations59

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Flow dataCapturing with SiLK

YAF – yet another flowmeter

• Produces IPFIX data from files or network traffic

• Can write to disk or push out over network

• Lightweight, easy to install

• Works well with SiLK tools60

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Flow dataCapturing – consolidating in SiLK

rwflowpack

• Part of the SiLK toolset

• Designed to receive input from multiple sensors and build a consolidated repository for analysis

• Just one of the pieces of a full sensor network.

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Flow dataAnalyzing with SiLK

SiLK tools

• Produced by CERT NetSA

• Relatively easy to use

• We’ve already been using them and have done a decent amount of writing on how to use them (check my transfer folder)

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Flow dataSiLK tools - conclusion

• Free, very powerful, extensible, pretty easy to use.

• Command line tools are great for things that we have running as daemons, but for visualizing flow data we can find a better interface. With the right tools, we can add better visualization.

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Flow dataVisualizing

Open source

• Afterglow + graphviz: cheap, but too much work to set up

Free/commercial

• Scrutinizer: quick and easy, consumes pretty much any flow data, free version is limited to 24 hours of data

• Lynxeon: belongs in the SIEM category, visualization tool is worth a mention though, 60 day trial

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Flow dataVisualization

http://www.networkuptime.com/tools/netflow/

http://freshmeat.net/search/?q=netflow&section=projects

TONS more

65Source: plixer.com, vizworld.com, networkuptime.com

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Flow dataContinuing research

Flowcon, Centaur Jam, etc.

• Come join us!

• Share your tools!

Statistical anomaly/group detection

• Complicated math

• New-ish technology, but worth a look if you’ve got a pile of netflow data that you’re sitting on.

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Day 1 Agenda and motivation Intro to forensic data types Working with PCAP data

What it looks like How to interpret it How to get it

Working with flow data What it looks like How to interpret it How to get it

Agenda

67

Day 2 PCAP and flow recap Working with logs and alerts

What they look like How to interpret them Getting them all in one place SIEM’s and their familiars

Fielding a monitoring solution

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PCAP reCAP

Most granular data we can collect

Takes a lot of resources to gather

Great for finding out how machines got pwned

Bad for figuring out what’s going on quickly

Can be converted into flow and alert data with the right tools

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FLOW reFLOW

Info about conversations on the network

Cheap and easy to collect

Quick to analyze with the right tools

Different analysis suites, formats

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Learning styles to use

More tool use?

More theory?

More collaboration!

You’ve got threats. I’ve got solutions.

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Questions about anything up to now?

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Day 1 Agenda and motivation Intro to forensic data types Working with PCAP data

What it looks like How to interpret it How to get it

Working with flow data What it looks like How to interpret it How to get it

Agenda

72

Day 2 PCAP and flow recap Working with logs and alerts

What they look like How to interpret them Getting them all in one place SIEM’s and their familiars

Fielding a monitoring solution

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Log/Alert dataWhat are we dealing with?

Logs are any continual text output stored by applications or devices in the process of their functioning.

Alerts are specialized logs produced by something when certain conditions occur that we had the foresight to set an alarm for. If a log is created saying that something we’ve set up a trigger for has happened, then we’ll get an alert.

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Log dataTypical sources

Web server

Web proxy

DNS

Operating system (/var/log/*)

SMTP

Whatever you’re using to manage logons

Building access controls

HVAC/ICS/SCADA/Power74

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Alert dataTypical sources

IDS

Firewall

Host based IDS

SIEM (Security Information & Event Manager)

Your server uptime and HA (high availability) stuff

What else?

Typically alerts are being produced because triggers that we’ve written are being tripped. If you’re not getting useful alerts, then you’ve configured something wrong!

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Alert dataRedundant IDS, etc?

Extra configuration

Add personnel

When one dies- “Multiple TippingPoint IPS Malformed Packet Detection Bypass Vulnerability”

Increased attack surface

More filtration, more rules, etc.76

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Alert dataLet’s go set up some triggers

Here’s how you go about getting good alerts

Find an incident that you want to be alerted about

Research what went over the network or got written to a log when that incident was occurring

Write a rule in your IDS or whatever to create an alert when that traffic is seen

Test your rule

Continue testing…

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Alert dataWhat will we use as a trigger?

Snort!

Open source, support packages available

Basis for Sourcefire appliances

Very popular, good support among SIMs

Very robust community providing rules, extensions, add ons, and anything else you can think of

Rule set subscriptions can be had from Sourcefire, and rules become free 30 days after they’re made available to subscribers

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Alert dataHow Snort works

1. Reads traffic from network

2. Decodes packets

3. Performs stream reassembly

4. Applies filters

5. Upon the first filter match, an alert is generated

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Alert dataWriting Snort rules

Fire up your VM’s. Time to go to work.

We’re going to look at how snort rules are written, what alerts look like, and how to write our own rules.

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Alert dataWriting better rules

Write to the vulnerability, not the exploit

Understand the base rate fallacy

Inspection chain

Test and tune your alerts

Dumbpig, external checking tools, profiling

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Log/Alert dataPriority of sources

Obviously not all data is equal, so here’s the basic order of which ones you should concentrate on first.

Alerts from security products (e.g. IDS, SIEM)

Netflow data, so you can track what those alerts are related to

OS event logs, so you can see what happened when those alerts were caused

What else?

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Log/Alert dataWhat does it look like?

Tons of formats, most of them customizable and flexible, some standards

Often application specific

Hard to read straight through, even using search…

83Source: screenshot from Windows Event Viewer

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Alert dataEvent formats

CEE – Common Event Expression

CVE – Vulnerability

CCE – Configuration

CWE – Weakness

CPE – Platform

CAPEC – Attack Patterns

…84

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Log/Alert dataDealing with disparate data

There’s too much text and not enough context. We need a way to get to the important logs and alerts quickly.

That’s why we use log managers and SIEM’s. They import the logs into one place, give us some pretty graphs, and (hopefully) make sure that the important entries catch our attention quickly.

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Log/Alert dataSIM, SEM, SIEM…

SIM = Security Information Management

SEM = Security Event Management

SIEM = Security Information and Event Management

SIM is for bookkeeping, SEM is for correlating data into events, and SIEM is a combo of the two.

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Log/Alert dataSIEMs

Perform event correlation, reduce false positives

Help filter logs and alerts to bring us the important data quickly under one monitor

Typically have a method for reading lots of log types

This is what you have running on a dedicated monitor in your lab for a technician to keep an eye on and call you when it turns red

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Log/Alert dataSome common managers/SIEMs

Splunk: free version will read 500MB/day of logs, has a decent interface to set up log parsing, technically just a log manager

ArcSight: popular SIEM suite, has its own log manager, could have a class just on Arcsight alone (and there are). BIG player in government and commercial sector, owing greatly to pushbutton compliance auditing.

RSA enVision: another big player, focused on appliances

88Disclaimer: the information expressed here is meant only to be informative and does not imply a recommendation

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Log/Alert dataUsing Splunk

Splunk is common enough that it’s worth your time to get to know. So for that reason, we’ll now take a quick look through its capabilities and the resources available for learning Splunk 4.0.

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Log/Alert dataSome common managers/SIEMs

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http://www.gartner.com/technology/media-products/reprints/nitrosecurity/article1/article1.htmlSource: Gartner (May 2010)

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Log/Alert dataArcsight event priority

Recalculated by ESM

Factors in:

• Normalized Severity S [0—10]

• Model of Confidence MCR[0—1]& Relevance

• Security History H [1—1.3]

• Asset Criticality C [0.8—1.3]

Priority = S * MCR * H * C

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Log/Alert dataArcsight event priority

Priority = S * MCR * H * C

MCR is the only factor that can drop P to 0

• Fully modeled asset, zero ports, zero vulnerabilities

• MCR = 0 Priority = 0

False positives fed into SIEM force H > 1

• Avalanche multiplication of false positives

Worst case: False positives + no asset modeling

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Source: arcsight console interface

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Log/Alert dataUsing SIEMs effectively

Understand the complexity of the tools you are using and allocate personnel appropriately.

Standardize what information your organization collects. Prioritize which information you set up collection for.

Regularly look at your flow data. Don’t depend on the SIEM to see everything.

Write new alert rules to handle your own particular threats.

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Deploying a monitoring solution

What you need to monitor a network will vary greatly depending on the size of the network, its purpose, the threats it will face, the technology used to build it, and countless other things.

Now go to www.ratemynetworkdiagram.com and let’s play pin the sensor on the network.

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Extended topics(if we have time)

Privacy/confidentiality laws

Attacking network monitoring devices

Evading network monitoring

Wireless monitoring

What products have you used and which ones did you like?

What else?95

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The End!

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